Building Reliable Systems: Lessons from Production

Reliability isn't a feature you add at the end—it's a foundation you build from the start. After years of maintaining production systems, I've learned that reliable systems share common patterns.

The Three Pillars

1. Fault Tolerance

Systems fail. Hardware fails, networks partition, dependencies go down. The question isn't if something will fail, but when.

// Circuit breaker pattern example
class CircuitBreaker {
  private failures = 0;
  private readonly threshold = 5;
  private state: 'closed' | 'open' | 'half-open' = 'closed';

  async execute<T>(fn: () => Promise<T>): Promise<T> {
    if (this.state === 'open') {
      throw new Error('Circuit breaker is open');
    }

    try {
      const result = await fn();
      this.onSuccess();
      return result;
    } catch (error) {
      this.onFailure();
      throw error;
    }
  }

  private onSuccess() {
    this.failures = 0;
    this.state = 'closed';
  }

  private onFailure() {
    this.failures++;
    if (this.failures >= this.threshold) {
      this.state = 'open';
      setTimeout(() => this.state = 'half-open', 60000);
    }
  }
}

2. Observability

You can't fix what you can't see. Structured logging, metrics, and traces aren't optional—they're how you understand what's happening in production.

3. Graceful Degradation

When a non-critical dependency fails, the system should continue operating with reduced functionality rather than failing entirely.

Design Patterns That Matter

Timeouts everywhere: Every network call needs a timeout. No exceptions.

Idempotency: Operations should be safe to retry. Design for at-least-once delivery.

Health checks: Deep health checks that actually verify the system can do work, not just that the process is running.

Conclusion

Reliability is earned through consistent application of patterns, rigorous testing, and learning from incidents. Start with these fundamentals, measure everything, and iterate.